Pandas Profiling Electronic Purchase Report on All Train

Dataset statistics

Number of variables	15
Number of observations	645816
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	90542
Duplicate rows (%)	14.0%
Total size in memory	73.9 MiB
Average record size in memory	120.0 B

Variable types

Numeric	9
Categorical	6

Alerts

`year` has constant value "2019"	Constant
`month` has constant value "11"	Constant
`Weekend` has constant value "0"	Constant
Dataset has 90542 (14.0%) duplicate rows	Duplicates
`NumOfEventsInJourney` is highly correlated with `NumSessions` and 2 other fields	High correlation
`NumSessions` is highly correlated with `NumOfEventsInJourney` and 3 other fields	High correlation
`interactionTime` is highly correlated with `NumSessions`	High correlation
`maxPrice` is highly correlated with `minPrice`	High correlation
`minPrice` is highly correlated with `maxPrice`	High correlation
`NumCart` is highly correlated with `NumOfEventsInJourney` and 3 other fields	High correlation
`NumView` is highly correlated with `NumOfEventsInJourney` and 4 other fields	High correlation
`InsessionCart` is highly correlated with `NumCart` and 1 other fields	High correlation
`year` is highly correlated with `Weekend` and 4 other fields	High correlation
`Weekend` is highly correlated with `year` and 4 other fields	High correlation
`Purchase` is highly correlated with `NumView`	High correlation
`timeOfDay` is highly correlated with `year` and 2 other fields	High correlation
`weekday` is highly correlated with `year` and 2 other fields	High correlation
`month` is highly correlated with `year` and 4 other fields	High correlation
`InsessionView` is highly skewed (γ1 = 28.41525841)	Skewed
`interactionTime` has 626461 (97.0%) zeros	Zeros
`NumCart` has 616828 (95.5%) zeros	Zeros
`NumView` has 33310 (5.2%) zeros	Zeros
`InsessionCart` has 613920 (95.1%) zeros	Zeros
`InsessionView` has 30664 (4.7%) zeros	Zeros

Reproduction

Analysis started	2022-09-27 02:06:55.602402
Analysis finished	2022-09-27 02:07:16.497782
Duration	20.9 seconds
Software version	pandas-profiling v3.3.0
Download configuration	config.json

NumOfEventsInJourney
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	11
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.033233924

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	1
Maximum	12
Range	11
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2018230987
Coefficient of variation (CV)	0.1953314675
Kurtosis	117.1425717
Mean	1.033233924
Median Absolute Deviation (MAD)	0
Skewness	8.150669616
Sum	667279
Variance	0.04073256317
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
1	626424	97.0%
2	17733	2.7%
3	1394	0.2%
4	187	< 0.1%
5	48	< 0.1%
6	13	< 0.1%
7	6	< 0.1%
9	5	< 0.1%
8	4	< 0.1%
10	1	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	626424	97.0%
2	17733	2.7%
3	1394	0.2%
4	187	< 0.1%
5	48	< 0.1%
6	13	< 0.1%
7	6	< 0.1%
8	4	< 0.1%
9	5	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
12	1	< 0.1%
10	1	< 0.1%
9	5	< 0.1%
8	4	< 0.1%
7	6	< 0.1%
6	13	< 0.1%
5	48	< 0.1%
4	187	< 0.1%
3	1394	0.2%
2	17733	2.7%

NumSessions
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.019697561

Minimum	1
Maximum	11
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	1
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	1
Maximum	11
Range	10
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.1562473221
Coefficient of variation (CV)	0.1532290829
Kurtosis	213.1474231
Mean	1.019697561
Median Absolute Deviation (MAD)	0
Skewness	10.92140517
Sum	658537
Variance	0.02441322566
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	634276	98.2%
2	10620	1.6%
3	760	0.1%
4	110	< 0.1%
5	27	< 0.1%
6	11	< 0.1%
8	4	< 0.1%
9	4	< 0.1%
7	3	< 0.1%
11	1	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	634276	98.2%
2	10620	1.6%
3	760	0.1%
4	110	< 0.1%
5	27	< 0.1%
6	11	< 0.1%
7	3	< 0.1%
8	4	< 0.1%
9	4	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
11	1	< 0.1%
9	4	< 0.1%
8	4	< 0.1%
7	3	< 0.1%
6	11	< 0.1%
5	27	< 0.1%
4	110	< 0.1%
3	760	0.1%
2	10620	1.6%
1	634276	98.2%

interactionTime
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	11987
Distinct (%)	1.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5817.817109

Minimum	0
Maximum	2526451
Zeros	626461
Zeros (%)	97.0%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	2526451
Range	2526451
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	71170.31405
Coefficient of variation (CV)	12.23316456
Kurtosis	353.2111249
Mean	5817.817109
Median Absolute Deviation (MAD)	0
Skewness	17.12366893
Sum	3757239374
Variance	5065213601
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	626461	97.0%
14	94	< 0.1%
16	83	< 0.1%
23	83	< 0.1%
22	81	< 0.1%
19	80	< 0.1%
11	76	< 0.1%
17	75	< 0.1%
8	75	< 0.1%
12	74	< 0.1%
Other values (11977)	18634	2.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	626461	97.0%
1	37	< 0.1%
2	35	< 0.1%
3	45	< 0.1%
4	63	< 0.1%
5	58	< 0.1%
6	45	< 0.1%
7	73	< 0.1%
8	75	< 0.1%
9	66	< 0.1%

Value	Count	Frequency (%)
2526451	1	< 0.1%
2520440	1	< 0.1%
2508763	1	< 0.1%
2494377	1	< 0.1%
2478403	1	< 0.1%
2473321	1	< 0.1%
2442933	1	< 0.1%
2436952	1	< 0.1%
2433976	1	< 0.1%
2419162	1	< 0.1%

maxPrice
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	30870
Distinct (%)	4.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	291.4637556

Minimum	0
Maximum	2574.07
Zeros	1799
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	0
5-th percentile	19.18
Q1	68.47
median	164.48
Q3	360.34
95-th percentile	991.7825
Maximum	2574.07
Range	2574.07
Interquartile range (IQR)	291.87

Descriptive statistics

Standard deviation	356.3124965
Coefficient of variation (CV)	1.222493328
Kurtosis	8.567720794
Mean	291.4637556
Median Absolute Deviation (MAD)	116.09
Skewness	2.575182739
Sum	188231956.8
Variance	126958.5952
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
154.42	2633	0.4%
89.84	2470	0.4%
334.37	2086	0.3%
231.64	1887	0.3%
0	1799	0.3%
308.63	1787	0.3%
643.23	1776	0.3%
308.86	1635	0.3%
51.46	1594	0.2%
82.63	1561	0.2%
Other values (30860)	626588	97.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1799	0.3%
0.77	3	< 0.1%
0.79	3	< 0.1%
0.8	2	< 0.1%
0.81	3	< 0.1%
0.83	6	< 0.1%
0.85	5	< 0.1%
0.87	6	< 0.1%
0.88	20	< 0.1%
0.9	14	< 0.1%

Value	Count	Frequency (%)
2574.07	73	< 0.1%
2574.04	114	< 0.1%
2573.99	12	< 0.1%
2573.81	51	< 0.1%
2573.79	121	< 0.1%
2573.76	1	< 0.1%
2573.45	5	< 0.1%
2573.29	2	< 0.1%
2573.17	1	< 0.1%
2572.23	104	< 0.1%

minPrice
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	30856
Distinct (%)	4.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	291.3639305

Minimum	0
Maximum	2574.07
Zeros	1813
Zeros (%)	0.3%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	0
5-th percentile	19.13
Q1	68.47
median	164.37
Q3	360.34
95-th percentile	991.13
Maximum	2574.07
Range	2574.07
Interquartile range (IQR)	291.87

Descriptive statistics

Standard deviation	356.2108656
Coefficient of variation (CV)	1.222563359
Kurtosis	8.574145299
Mean	291.3639305
Median Absolute Deviation (MAD)	115.98
Skewness	2.575915721
Sum	188167488.2
Variance	126886.1808
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
154.42	2644	0.4%
89.84	2467	0.4%
334.37	2084	0.3%
231.64	1883	0.3%
0	1813	0.3%
308.63	1776	0.3%
643.23	1772	0.3%
308.86	1625	0.3%
51.46	1596	0.2%
82.63	1561	0.2%
Other values (30846)	626595	97.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1813	0.3%
0.77	3	< 0.1%
0.79	3	< 0.1%
0.8	2	< 0.1%
0.81	3	< 0.1%
0.83	6	< 0.1%
0.85	5	< 0.1%
0.87	6	< 0.1%
0.88	20	< 0.1%
0.9	14	< 0.1%

Value	Count	Frequency (%)
2574.07	73	< 0.1%
2574.04	113	< 0.1%
2573.99	12	< 0.1%
2573.81	51	< 0.1%
2573.79	121	< 0.1%
2573.76	1	< 0.1%
2573.45	5	< 0.1%
2573.29	2	< 0.1%
2573.17	1	< 0.1%
2572.23	104	< 0.1%

NumCart
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.04623607963

Minimum	0
Maximum	9
Zeros	616828
Zeros (%)	95.5%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2173800252
Coefficient of variation (CV)	4.701523721
Kurtosis	32.6556108
Mean	0.04623607963
Median Absolute Deviation (MAD)	0
Skewness	5.00299969
Sum	29860
Variance	0.04725407533
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=9)

Value	Count	Frequency (%)
0	616828	95.5%
1	28210	4.4%
2	710	0.1%
3	55	< 0.1%
4	7	< 0.1%
5	3	< 0.1%
9	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	616828	95.5%
1	28210	4.4%
2	710	0.1%
3	55	< 0.1%
4	7	< 0.1%
5	3	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
9	1	< 0.1%
7	1	< 0.1%
6	1	< 0.1%
5	3	< 0.1%
4	7	< 0.1%
3	55	< 0.1%
2	710	0.1%
1	28210	4.4%
0	616828	95.5%

NumView
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.9729412093

Minimum	0
Maximum	9
Zeros	33310
Zeros (%)	5.2%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	1
median	1
Q3	1
95-th percentile	1
Maximum	9
Range	9
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2832555948
Coefficient of variation (CV)	0.2911333101
Kurtosis	21.43012545
Mean	0.9729412093
Median Absolute Deviation (MAD)	0
Skewness	-0.0201645368
Sum	628341
Variance	0.080233732
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
1	597891	92.6%
0	33310	5.2%
2	13613	2.1%
3	857	0.1%
4	106	< 0.1%
5	21	< 0.1%
6	10	< 0.1%
7	3	< 0.1%
9	3	< 0.1%
8	2	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	33310	5.2%
1	597891	92.6%
2	13613	2.1%
3	857	0.1%
4	106	< 0.1%
5	21	< 0.1%
6	10	< 0.1%
7	3	< 0.1%
8	2	< 0.1%
9	3	< 0.1%

Value	Count	Frequency (%)
9	3	< 0.1%
8	2	< 0.1%
7	3	< 0.1%
6	10	< 0.1%
5	21	< 0.1%
4	106	< 0.1%
3	857	0.1%
2	13613	2.1%
1	597891	92.6%
0	33310	5.2%

InsessionCart
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.0508116863

Minimum	0
Maximum	8
Zeros	613920
Zeros (%)	95.1%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	8
Range	8
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.2268888315
Coefficient of variation (CV)	4.465288362
Kurtosis	26.38035737
Mean	0.0508116863
Median Absolute Deviation (MAD)	0
Skewness	4.664764099
Sum	32815
Variance	0.05147854186
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
0	613920	95.1%
1	31065	4.8%
2	766	0.1%
3	52	< 0.1%
4	8	< 0.1%
5	3	< 0.1%
8	1	< 0.1%
7	1	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	613920	95.1%
1	31065	4.8%
2	766	0.1%
3	52	< 0.1%
4	8	< 0.1%
5	3	< 0.1%
7	1	< 0.1%
8	1	< 0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	1	< 0.1%
5	3	< 0.1%
4	8	< 0.1%
3	52	< 0.1%
2	766	0.1%
1	31065	4.8%
0	613920	95.1%

InsessionView
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	21
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.198116801

Minimum	0
Maximum	68
Zeros	30664
Zeros (%)	4.7%
Negative	0
Negative (%)	0.0%
Memory size	4.9 MiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	1
Q3	1
95-th percentile	2
Maximum	68
Range	68
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	0.8756566779
Coefficient of variation (CV)	0.7308608619
Kurtosis	1911.400458
Mean	1.198116801
Median Absolute Deviation (MAD)	0
Skewness	28.41525841
Sum	773763
Variance	0.7667746176
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
1	500860	77.6%
2	87158	13.5%
0	30664	4.7%
3	18927	2.9%
4	5300	0.8%
5	1662	0.3%
6	686	0.1%
7	233	< 0.1%
8	78	< 0.1%
9	66	< 0.1%
Other values (11)	182	< 0.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	30664	4.7%
1	500860	77.6%
2	87158	13.5%
3	18927	2.9%
4	5300	0.8%
5	1662	0.3%
6	686	0.1%
7	233	< 0.1%
8	78	< 0.1%
9	66	< 0.1%

Value	Count	Frequency (%)
68	34	< 0.1%
34	17	< 0.1%
32	21	< 0.1%
23	12	< 0.1%
22	14	< 0.1%
20	10	< 0.1%
19	21	< 0.1%
13	5	< 0.1%
12	17	< 0.1%
11	7	< 0.1%

year
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.9 MiB

2019	645816

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	2583264
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2019
2nd row	2019
3rd row	2019
4th row	2019
5th row	2019

Common Values

Value	Count	Frequency (%)
2019	645816	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
2019	645816	100.0%

Most occurring characters

Value	Count	Frequency (%)
2	645816	25.0%
0	645816	25.0%
1	645816	25.0%
9	645816	25.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2583264	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	645816	25.0%
0	645816	25.0%
1	645816	25.0%
9	645816	25.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2583264	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	645816	25.0%
0	645816	25.0%
1	645816	25.0%
9	645816	25.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2583264	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	645816	25.0%
0	645816	25.0%
1	645816	25.0%
9	645816	25.0%

month
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.9 MiB

11	645816

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	1291632
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	11
2nd row	11
3rd row	11
4th row	11
5th row	11

Common Values

Value	Count	Frequency (%)
11	645816	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
11	645816	100.0%

Most occurring characters

Value	Count	Frequency (%)
1	1291632	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	1291632	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1291632	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	1291632	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1291632	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1291632	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1291632	100.0%

weekday
Categorical

HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.9 MiB

Sat	126504
Fr	123677
Sun	110305
Thu	78638
Mon	71479
Other values (2)	135213

Length

Max length	3
Median length	3
Mean length	2.808494989
Min length	2

Characters and Unicode

Total characters	1813771
Distinct characters	14
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Sat
2nd row	Fr
3rd row	Thu
4th row	Mon
5th row	Tue

Common Values

Value	Count	Frequency (%)
Sat	126504	19.6%
Fr	123677	19.2%
Sun	110305	17.1%
Thu	78638	12.2%
Mon	71479	11.1%
Tue	67850	10.5%
Wed	67363	10.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
sat	126504	19.6%
fr	123677	19.2%
sun	110305	17.1%
thu	78638	12.2%
mon	71479	11.1%
tue	67850	10.5%
wed	67363	10.4%

Most occurring characters

Value	Count	Frequency (%)
u	256793	14.2%
S	236809	13.1%
n	181784	10.0%
T	146488	8.1%
e	135213	7.5%
a	126504	7.0%
t	126504	7.0%
F	123677	6.8%
r	123677	6.8%
h	78638	4.3%
Other values (4)	277684	15.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	1167955	64.4%
Uppercase Letter	645816	35.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	256793	22.0%
n	181784	15.6%
e	135213	11.6%
a	126504	10.8%
t	126504	10.8%
r	123677	10.6%
h	78638	6.7%
o	71479	6.1%
d	67363	5.8%

Uppercase Letter

Value	Count	Frequency (%)
S	236809	36.7%
T	146488	22.7%
F	123677	19.2%
M	71479	11.1%
W	67363	10.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	1813771	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
u	256793	14.2%
S	236809	13.1%
n	181784	10.0%
T	146488	8.1%
e	135213	7.5%
a	126504	7.0%
t	126504	7.0%
F	123677	6.8%
r	123677	6.8%
h	78638	4.3%
Other values (4)	277684	15.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	1813771	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
u	256793	14.2%
S	236809	13.1%
n	181784	10.0%
T	146488	8.1%
e	135213	7.5%
a	126504	7.0%
t	126504	7.0%
F	123677	6.8%
r	123677	6.8%
h	78638	4.3%
Other values (4)	277684	15.3%

timeOfDay
Categorical

HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.9 MiB

Afternoon	165214
EarlyMorning	136248
Evening	110578
Morning	103407
Dawn	80495
Other values (2)	49874

Length

Max length	12
Median length	9
Mean length	7.985099471
Min length	4

Characters and Unicode

Total characters	5156905
Distinct characters	19
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Morning
2nd row	Dawn
3rd row	Afternoon
4th row	Noon
5th row	Noon

Common Values

Value	Count	Frequency (%)
Afternoon	165214	25.6%
EarlyMorning	136248	21.1%
Evening	110578	17.1%
Morning	103407	16.0%
Dawn	80495	12.5%
Noon	34242	5.3%
Night	15632	2.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
afternoon	165214	25.6%
earlymorning	136248	21.1%
evening	110578	17.1%
morning	103407	16.0%
dawn	80495	12.5%
noon	34242	5.3%
night	15632	2.4%

Most occurring characters

Value	Count	Frequency (%)
n	1145631	22.2%
o	638567	12.4%
r	541117	10.5%
i	365865	7.1%
g	365865	7.1%
e	275792	5.3%
E	246826	4.8%
M	239655	4.6%
a	216743	4.2%
t	180846	3.5%
Other values (9)	939998	18.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4374841	84.8%
Uppercase Letter	782064	15.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	1145631	26.2%
o	638567	14.6%
r	541117	12.4%
i	365865	8.4%
g	365865	8.4%
e	275792	6.3%
a	216743	5.0%
t	180846	4.1%
f	165214	3.8%
l	136248	3.1%
Other values (4)	342953	7.8%

Uppercase Letter

Value	Count	Frequency (%)
E	246826	31.6%
M	239655	30.6%
A	165214	21.1%
D	80495	10.3%
N	49874	6.4%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5156905	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	1145631	22.2%
o	638567	12.4%
r	541117	10.5%
i	365865	7.1%
g	365865	7.1%
e	275792	5.3%
E	246826	4.8%
M	239655	4.6%
a	216743	4.2%
t	180846	3.5%
Other values (9)	939998	18.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5156905	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	1145631	22.2%
o	638567	12.4%
r	541117	10.5%
i	365865	7.1%
g	365865	7.1%
e	275792	5.3%
E	246826	4.8%
M	239655	4.6%
a	216743	4.2%
t	180846	3.5%
Other values (9)	939998	18.2%

Weekend
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.9 MiB

0	645816

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	645816
Distinct characters	1
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	645816	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	645816	100.0%

Most occurring characters

Value	Count	Frequency (%)
0	645816	100.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	645816	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	645816	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	645816	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	645816	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	645816	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	645816	100.0%

Purchase
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	4.9 MiB

0	636839
1	8977

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	645816
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	636839	98.6%
1	8977	1.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	636839	98.6%
1	8977	1.4%

Most occurring characters

Value	Count	Frequency (%)
0	636839	98.6%
1	8977	1.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	645816	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	636839	98.6%
1	8977	1.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	645816	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	636839	98.6%
1	8977	1.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	645816	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	636839	98.6%
1	8977	1.4%

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	NumOfEventsInJourney	NumSessions	maxPrice	minPrice	NumView	InsessionView	year	month	weekday	timeOfDay
0	1	1	154.41	154.41	1	1	2019	11	Sat	Morning
1	1	1	92.67	92.67	1	1	2019	11	Fr	Dawn
2	1	1	155.71	155.71	1	1	2019	11	Thu	Afternoon
3	1	1	898.32	898.32	1	1	2019	11	Mon	Noon
4	1	1	146.21	146.21	1	1	2019	11	Tue	Noon
5	1	1	244.54	244.54	1	1	2019	11	Sat	Noon
6	1	1	234.24	234.24	1	1	2019	11	Sat	Morning
7	1	1	463.31	463.31	1	1	2019	11	Wed	Evening
8	1	1	253.25	253.25	1	1	2019	11	Thu	Afternoon
9	1	1	450.18	450.18	1	1	2019	11	Mon	Morning

Last rows

	NumOfEventsInJourney	NumSessions	maxPrice	minPrice	NumView	InsessionView	year	month	weekday	timeOfDay
645806	1	1	2239.18	2239.18	1	1	2019	11	Mon	EarlyMorning
645807	1	1	121.24	121.24	1	1	2019	11	Sat	Dawn
645808	1	1	615.20	615.20	1	1	2019	11	Sat	Evening
645809	1	1	2254.82	2254.82	1	2	2019	11	Sat	Morning
645810	1	1	991.06	991.06	1	1	2019	11	Tue	Dawn
645811	1	1	128.67	128.67	1	2	2019	11	Sat	EarlyMorning
645812	1	1	244.51	244.51	1	1	2019	11	Thu	EarlyMorning
645813	1	1	152.82	152.82	1	1	2019	11	Sun	EarlyMorning
645814	1	1	190.22	190.22	1	1	2019	11	Wed	Evening
645815	1	1	24.41	24.41	1	1	2019	11	Wed	Afternoon

Most frequently occurring

	NumOfEventsInJourney	NumSessions	maxPrice	minPrice	NumView	InsessionView	year	month	weekday	timeOfDay	# duplicates
42570	1	1	154.42	154.42	1	1	2019	11	Fr	Afternoon	138
83967	1	1	914.00	914.00	1	1	2019	11	Sat	EarlyMorning	123
56953	1	1	243.49	243.49	1	1	2019	11	Sat	EarlyMorning	122
36962	1	1	128.42	128.42	1	1	2019	11	Sun	EarlyMorning	119
36960	1	1	128.42	128.42	1	1	2019	11	Sun	Afternoon	113
42586	1	1	154.42	154.42	1	1	2019	11	Sat	EarlyMorning	111
83960	1	1	914.00	914.00	1	1	2019	11	Fr	Dawn	110
42593	1	1	154.42	154.42	1	1	2019	11	Sun	EarlyMorning	107
36953	1	1	128.42	128.42	1	1	2019	11	Sat	Afternoon	106
27274	1	1	89.84	89.84	1	1	2019	11	Sat	Afternoon	104

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks